vignettes/articles/accessing_project_data.Rmd
accessing_project_data.RmdThis article walks through, in detail, accessing data specific to
projects, primarily via mermaid_get_project_data().
To access data related to your MERMAID projects, first obtain a list
of your projects with mermaid_get_my_projects().
At this point, you will have to authenticate to the Collect app. R will help you do this automatically by opening a browser window for you to log in to Collect, either via Google sign-in or username and password - however you normally do!
Once you’ve logged in, come back to R. Your login credentials will be stored for a day, until they expire, and you will need to login again. The package handles the expiration for you, so just log in again when prompted.
library(mermaidr)
my_projects <- mermaid_get_my_projects()
my_projects
#> # A tibble: 12 × 14
#> id name countries num_sites tags notes status data_policy_bel…
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e691… TWP Gi… Indonesia 14 "WCS Ind… "" Open Private
#> 2 170e71… 2018_V… Fiji 10 "WCS Fij… "This is… Open Private
#> 3 2d6cee… WCS Mo… Mozambique 74 "WCS Moz… "Databas… Open Private
#> 4 3a9ecb… Aceh J… Indonesia 18 "Vibrant… "" Open Private
#> 5 408067… Madaga… Madagascar 74 "WCS Mad… "MACMON … Open Private
#> 6 4d23d2… Madaga… Madagascar 16 "WCS Mad… "Monitor… Open Public Summary
#> 7 507d1a… Karimu… Indonesia 43 "Vibrant… "" Open Private
#> 8 5679ef… Madaga… Madagascar 33 "WCS Mad… "" Open Public Summary
#> 9 75ef7a… Kubula… Fiji 78 "WCS Fij… "" Open Private
#> 10 9de827… XPDC K… Indonesia 37 "" "XPDC Ke… Open Private
#> 11 a1b7ff… Great … Fiji 76 "Fiji Mi… "" Open Private
#> 12 e1efb1… 2016_N… Fiji 8 "WCS Fij… "Namena … Open Private
#> # … with 6 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, created_on <chr>, updated_on <chr>This function returns information on your projects, including project countries, the number of sites, tags, data policies, and more.
To filter for specific projects, you can use the filter
function from dplyr:
library(dplyr)
indonesia_projects <- my_projects %>%
filter(countries == "Indonesia")
indonesia_projects
#> # A tibble: 4 × 14
#> id name countries num_sites tags notes status data_policy_bel…
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915… TWP Gi… Indonesia 14 "WCS In… "" Open Private
#> 2 3a9ecb7… Aceh J… Indonesia 18 "Vibran… "" Open Private
#> 3 507d1af… Karimu… Indonesia 43 "Vibran… "" Open Private
#> 4 9de8278… XPDC K… Indonesia 37 "" "XPDC Kei … Open Private
#> # … with 6 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, created_on <chr>, updated_on <chr>Alternatively, you can search your projects using
mermaid_search_my_projects(), narrowing projects down by
name, countries, or tags:
mermaid_search_my_projects(countries = "Indonesia")
#> # A tibble: 4 × 14
#> id name countries num_sites tags notes status data_policy_bel…
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915… TWP Gi… Indonesia 14 "WCS In… "" Open Private
#> 2 3a9ecb7… Aceh J… Indonesia 18 "Vibran… "" Open Private
#> 3 507d1af… Karimu… Indonesia 43 "Vibran… "" Open Private
#> 4 9de8278… XPDC K… Indonesia 37 "" "XPDC Kei … Open Private
#> # … with 6 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, created_on <chr>, updated_on <chr>Then, you can start to access data about your projects, like project
sites via mermaid_get_project_sites():
indonesia_projects %>%
mermaid_get_project_sites()
#> # A tibble: 112 × 13
#> project id name notes latitude longitude country reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Karimunja… a7635ca… Gentin… "" -5.86 111. Indone… fringing back reef
#> 2 Aceh Jaya… 5436053… Wisata… "" 5.04 95.4 Indone… fringing fore reef
#> 3 Aceh Jaya… b7d5cf6… Rehabi… "" 4.84 95.4 Indone… fringing fore reef
#> 4 Karimunja… 03685be… Menyaw… "" -5.80 110. Indone… fringing fore reef
#> 5 Aceh Jaya… 38f75ee… Pulau … "" 5.08 95.3 Indone… fringing back reef
#> 6 Karimunja… 21aec9f… Batu P… "" -5.81 110. Indone… fringing back reef
#> 7 Karimunja… 371b3e9… Tanjun… "" -5.83 110. Indone… fringing back reef
#> 8 Karimunja… 43d3d64… Legon … "" -5.87 110. Indone… fringing back reef
#> 9 Karimunja… 9ec6f18… Cemara… "" -5.80 110. Indone… fringing back reef
#> 10 Karimunja… e23aaba… Tanjun… "" -5.86 110. Indone… fringing back reef
#> # … with 102 more rows, and 4 more variables: exposure <chr>, predecessor <chr>,
#> # created_on <chr>, updated_on <chr>Or the managements for your projects via
mermaid_get_project_managements():
indonesia_projects %>%
mermaid_get_project_managements()
#> # A tibble: 24 × 17
#> project id name name_secondary notes est_year no_take periodic_closure
#> <chr> <chr> <chr> <chr> <chr> <int> <lgl> <lgl>
#> 1 TWP Gili Sulat Lawang 0975… Zona… "Core Zone" "" 2013 TRUE FALSE
#> 2 TWP Gili Sulat Lawang 636c… Luar… "Open Access" "" 2020 FALSE FALSE
#> 3 TWP Gili Sulat Lawang bc4e… Zona… "Fisheries Ut… "" 2013 FALSE FALSE
#> 4 TWP Gili Sulat Lawang f557… Zona… "Sustainable … "" 2013 FALSE FALSE
#> 5 Aceh Jaya Coastal Park 0f0f… Open "" "" 2019 FALSE FALSE
#> 6 Aceh Jaya Coastal Park 1498… Tour… "" "" 2019 TRUE FALSE
#> 7 Aceh Jaya Coastal Park 646c… Fish… "" "" 2019 FALSE FALSE
#> 8 Aceh Jaya Coastal Park a579… Aqua… "" "" 2019 FALSE FALSE
#> 9 Aceh Jaya Coastal Park a803… Open… "" "" 2019 FALSE FALSE
#> 10 Aceh Jaya Coastal Park cc92… Core… "" "" 2019 TRUE FALSE
#> # … with 14 more rows, and 9 more variables: open_access <lgl>, size_limits <lgl>,
#> # gear_restriction <lgl>, species_restriction <lgl>, compliance <chr>,
#> # predecessor <lgl>, parties <chr>, created_on <chr>, updated_on <chr>You can also access data on your projects’ Fish Belt, Benthic LIT, Benthic PIT, Bleaching, and Habitat Complexity methods. The details are in the following sections.
To access Fish Belt data for a project, use
mermaid_get_project_data() with
method = "fishbelt".
You can access individual observations (i.e., a record of each
observation) by setting data = "observations":
xpdc <- my_projects %>%
filter(name == "XPDC Kei Kecil 2018")
xpdc %>%
mermaid_get_project_data(method = "fishbelt", data = "observations")
#> # A tibble: 3,069 × 65
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 3 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 4 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 5 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 6 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 7 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 8 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 9 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 10 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> # … with 3,059 more rows, and 56 more variables: reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, …You can access sample units data, which are observations aggregated to the sample units level. Fish belt sample units contain total biomass in kg/ha per sample unit, by trophic group and by fish family:
xpdc %>%
mermaid_get_project_data("fishbelt", "sampleunits")
#> # A tibble: 246 × 79
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 3 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 4 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 5 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 6 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 7 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 8 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 9 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 10 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> # … with 236 more rows, and 70 more variables: reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, …And finally, sample events data, which are aggregated further, to the sample event level. Fish belt sample events contain mean total biomass in kg/ha per sample event, by trophic group and by fish family:
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data("fishbelt", "sampleevents")
xpdc_sample_events
#> # A tibble: 46 × 69
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 3 XPDC K… NA Indone… KE04 -5.58 132. fringing crest exposed
#> 4 XPDC K… NA Indone… KE05 -5.47 133. fringing crest exposed
#> 5 XPDC K… NA Indone… KE06 -5.52 132. fringing crest exposed
#> 6 XPDC K… NA Indone… KE07 -5.57 133. fringing crest exposed
#> 7 XPDC K… NA Indone… KE08 -5.55 133. fringing crest exposed
#> 8 XPDC K… NA Indone… KE09 -5.60 133. fringing fore reef semi-exposed
#> 9 XPDC K… NA Indone… KE10 -5.57 133. fringing crest exposed
#> 10 XPDC K… NA Indone… KE11 -5.59 133. fringing crest exposed
#> # … with 36 more rows, and 60 more variables: tide <chr>, current <chr>,
#> # visibility <chr>, aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, management_secondary <chr>, …To access Benthic LIT data, use
mermaid_get_project_data() with
method = "benthiclit".
mozambique <- my_projects %>%
filter(name == "WCS Mozambique Coral Reef Monitoring")
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "observations")
#> # A tibble: 1,569 × 56
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 2 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 3 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 4 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 5 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 6 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 7 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 8 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 9 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 10 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> # … with 1,559 more rows, and 47 more variables: reef_slope <lgl>, tide <chr>,
#> # current <lgl>, visibility <lgl>, relative_depth <lgl>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, …You can access sample units and sample events the same way.
For Benthic LIT, sample units contain percent cover per sample unit, by benthic category. Sample events contain mean percent cover per sample event, by benthic category.
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "sampleunits")
#> # A tibble: 63 × 65
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 2 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 3 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 4 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 5 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 6 WCS Mo… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef sheltered
#> 7 WCS Mo… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered
#> 8 WCS Mo… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered
#> 9 WCS Mo… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered
#> 10 WCS Mo… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef sheltered
#> # … with 53 more rows, and 56 more variables: reef_slope <lgl>, tide <chr>,
#> # current <lgl>, visibility <lgl>, relative_depth <lgl>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, …To access Benthic LIT data, change method to
“benthicpit”:
xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = "observations")
#> # A tibble: 11,100 × 57
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 3 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 4 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 5 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 6 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 7 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 8 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 9 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 10 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> # … with 11,090 more rows, and 48 more variables: reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, …You can access sample units and sample events the same way, and the data format is the same as Benthic LIT.
You can return both sample units and sample events by setting the
data argument. This will return a list of two data frames:
one containing sample units, and the other sample events.
xpdc_sample_units_events <- xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = c("sampleunits", "sampleevents"))
names(xpdc_sample_units_events)
#> [1] "sampleunits" "sampleevents"
xpdc_sample_units_events[["sampleunits"]]
#> # A tibble: 111 × 66
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 3 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 4 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 5 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 6 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 7 XPDC K… NA Indone… KE04 -5.58 132. fringing crest exposed
#> 8 XPDC K… NA Indone… KE04 -5.58 132. fringing crest exposed
#> 9 XPDC K… NA Indone… KE04 -5.58 132. fringing crest exposed
#> 10 XPDC K… NA Indone… KE05 -5.47 133. fringing crest exposed
#> # … with 101 more rows, and 57 more variables: reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, …To access Bleaching data, set method to “bleaching”.
There are two types of observations data for the Bleaching method:
Colonies Bleached and Percent Cover. These are both returned when
pulling observations data, in a list:
bleaching_obs <- mozambique %>%
mermaid_get_project_data("bleaching", "observations")
names(bleaching_obs)
#> [1] "colonies_bleached" "percent_cover"
bleaching_obs[["colonies_bleached"]]
#> # A tibble: 1,814 × 57
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 2 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 3 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 4 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 5 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 6 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 7 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 8 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 9 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 10 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> # … with 1,804 more rows, and 48 more variables: tide <lgl>, current <lgl>,
#> # visibility <lgl>, relative_depth <lgl>, aca_geomorphic <chr>,
#> # aca_benthic <chr>, andrello_grav_nc <dbl>, andrello_sediment <dbl>,
#> # andrello_nutrient <dbl>, andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, management <chr>, …The sample units and sample events data contain summaries of both Colonies Bleached and Percent Cover:
mozambique %>%
mermaid_get_project_data("bleaching", "sampleevents")
#> # A tibble: 62 × 54
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 2 WCS Mo… WCS … Mozamb… Baby… -11.0 40.7 fringing fore reef exposed
#> 3 WCS Mo… WCS … Mozamb… Balu… -22.0 35.5 patch fore reef exposed
#> 4 WCS Mo… WCS … Mozamb… Dos … -12.1 40.6 lagoon back reef sheltered
#> 5 WCS Mo… WCS … Mozamb… Fing… -12.9 40.6 fringing fore reef exposed
#> 6 WCS Mo… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 7 WCS Mo… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 8 WCS Mo… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef sheltered
#> 9 WCS Mo… WCS … Mozamb… Libe… -14.5 40.7 fringing back reef sheltered
#> 10 WCS Mo… WCS … Mozamb… Ligh… -12.3 40.6 fringing fore reef exposed
#> # … with 52 more rows, and 45 more variables: tide <lgl>, current <lgl>,
#> # visibility <lgl>, aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, management_secondary <chr>, …Finally, to access Habitat Complexity data, set method
to “habitatcomplexity”. As with all other methods, you can access
observations, sample units, and sample events:
xpdc %>%
mermaid_get_project_data("habitatcomplexity", "sampleevents")
#> # A tibble: 2 × 45
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC Ke… NA Indone… KE22 -5.85 133. fringing fore reef exposed
#> 2 XPDC Ke… NA Indone… KE24 -5.93 133. fringing fore reef exposed
#> # … with 36 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # aca_geomorphic <chr>, aca_benthic <chr>, andrello_grav_nc <dbl>,
#> # andrello_sediment <dbl>, andrello_nutrient <dbl>, andrello_pop_count <dbl>,
#> # andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, management_secondary <chr>, …To pull data for both fish belt and benthic PIT methods, you can set
method to include both.
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data(method = c("fishbelt", "benthicpit"), data = "sampleevents")The result is a list of data frames, containing sample events for both fish belt and benthic PIT methods:
names(xpdc_sample_events)
#> [1] "fishbelt" "benthicpit"
xpdc_sample_events[["benthicpit"]]
#> # A tibble: 38 × 56
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 XPDC K… NA Indone… KE02 -5.44 133. fringing crest exposed
#> 2 XPDC K… NA Indone… KE03 -5.61 132. fringing crest exposed
#> 3 XPDC K… NA Indone… KE04 -5.58 132. fringing crest exposed
#> 4 XPDC K… NA Indone… KE05 -5.47 133. fringing crest exposed
#> 5 XPDC K… NA Indone… KE06 -5.52 132. fringing crest exposed
#> 6 XPDC K… NA Indone… KE07 -5.57 133. fringing crest exposed
#> 7 XPDC K… NA Indone… KE08 -5.55 133. fringing crest exposed
#> 8 XPDC K… NA Indone… KE09 -5.60 133. fringing fore reef semi-exposed
#> 9 XPDC K… NA Indone… KE10 -5.57 133. fringing crest exposed
#> 10 XPDC K… NA Indone… KE11 -5.59 133. fringing crest exposed
#> # … with 28 more rows, and 47 more variables: tide <chr>, current <chr>,
#> # visibility <chr>, aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, management_secondary <chr>, …Alternatively, you can set method to “all” to pull for
all methods! Similarly, you can set data to “all” to pull
all types of data:
all_project_data <- xpdc %>%
mermaid_get_project_data(method = "all", data = "all", limit = 1)
names(all_project_data)
#> [1] "fishbelt" "benthiclit" "benthicpit" "bleaching"
#> [5] "habitatcomplexity"
names(all_project_data[["benthicpit"]])
#> [1] "observations" "sampleunits" "sampleevents"Pulling data for multiple projects is the exact same, except there
will be an additional “project” column at the beginning to distinguish
which projects the data comes from. Recall that my_projects
contains six projects:
my_projects
#> # A tibble: 12 × 14
#> id name countries num_sites tags notes status data_policy_bel…
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e691… TWP Gi… Indonesia 14 "WCS Ind… "" Open Private
#> 2 170e71… 2018_V… Fiji 10 "WCS Fij… "This is… Open Private
#> 3 2d6cee… WCS Mo… Mozambique 74 "WCS Moz… "Databas… Open Private
#> 4 3a9ecb… Aceh J… Indonesia 18 "Vibrant… "" Open Private
#> 5 408067… Madaga… Madagascar 74 "WCS Mad… "MACMON … Open Private
#> 6 4d23d2… Madaga… Madagascar 16 "WCS Mad… "Monitor… Open Public Summary
#> 7 507d1a… Karimu… Indonesia 43 "Vibrant… "" Open Private
#> 8 5679ef… Madaga… Madagascar 33 "WCS Mad… "" Open Public Summary
#> 9 75ef7a… Kubula… Fiji 78 "WCS Fij… "" Open Private
#> 10 9de827… XPDC K… Indonesia 37 "" "XPDC Ke… Open Private
#> 11 a1b7ff… Great … Fiji 76 "Fiji Mi… "" Open Private
#> 12 e1efb1… 2016_N… Fiji 8 "WCS Fij… "Namena … Open Private
#> # … with 6 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_habitatcomplexity <chr>,
#> # data_policy_bleachingqc <chr>, created_on <chr>, updated_on <chr>
my_projects %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1)
#> # A tibble: 11 × 82
#> project tags country site latitude longitude reef_type reef_zone reef_exposure
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 TWP Gi… WCS … Indone… Peda… -8.28 117. fringing crest exposed
#> 2 2018_V… WCS … Fiji VIR1 -17.3 178. barrier fore reef exposed
#> 3 WCS Mo… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef semi-exposed
#> 4 Aceh J… WCS … Indone… Abah… 4.99 95.4 fringing fore reef exposed
#> 5 Madaga… WCS … Madaga… Kisi… -13.6 48.1 fringing fore reef exposed
#> 6 Karimu… WCS … Indone… Batu… -5.81 110. fringing back reef semi-exposed
#> 7 Madaga… WCS … Madaga… Anta… -16.4 49.8 fringing fore reef semi-exposed
#> 8 Kubula… WCS … Fiji C13 -17.0 179. barrier fore reef semi-exposed
#> 9 XPDC K… <NA> Indone… KE02 -5.44 133. fringing crest exposed
#> 10 Great … Fiji… Fiji BA02 -17.4 178. atoll back reef very shelter…
#> 11 2016_N… WCS … Fiji C3 -17.1 179. barrier fore reef exposed
#> # … with 73 more variables: tide <chr>, current <chr>, visibility <chr>,
#> # aca_geomorphic <chr>, aca_benthic <chr>, andrello_grav_nc <dbl>,
#> # andrello_sediment <dbl>, andrello_nutrient <dbl>, andrello_pop_count <dbl>,
#> # andrello_num_ports <dbl>, andrello_reef_value <dbl>,
#> # andrello_cumul_score <dbl>, beyer_score <dbl>, beyer_scorecn <dbl>,
#> # beyer_scorecy <dbl>, beyer_scorepfc <dbl>, beyer_scoreth <dbl>,
#> # beyer_scoretr <dbl>, management <chr>, management_secondary <chr>, …Note the limit argument here, which just limits the data
pulled to one record (per project, method, and data combination). This
is useful if you want to get a preview of what your data will look like
without having to pull it all in.